A few Challenges to Make Machine Learning Easy

Speaker:  Dr. Francisco J Martin

Event Details In the age of data, Machine Learning is the key component to make data-driven decisions, develop smart applications, and build predictive analytics. However, Machine Learning is complex. The current tools are complicated and do not scale well. Most solutions are costly, easily involving hundreds of thousands of dollars and substantial resources. Additionally, experts with industry experience are very scarce. BigML is building a scalable, cloud-based service that makes Machine Learning easy or, at least,  lowers the barriers that most developers and business folks face to learn from data. In this talk, I will first demo BigML and then describe the efforts, highlight some of the key findings, and discuss some of the challenges from a technical, user, and business perspective, related to developing a Machine Learning service for the masses.

Speaker Bio In 1999, Francisco founded iSOCO-Intelligent Software Components, SA. iSOCO specializes in business solutions built on top of Artificial Intelligence and pioneered research and applications of semantic web technologies.  In 2004, Francisco founded Strands, Inc. Strands is a leading developer of recommendation and personalization technologies. Strands pioneered research and applications of social recommendation technologies in several domains (music, videos, personal finance, sports, etc). In 2011, Francisco co-founded BigML, Inc to unleash the power of machine learning as a service. BigML is creating the simplest, easiest-to-use and most seamless-to-integrate Machine Learning cloud-based service. Francisco holds a Ph.D. in Artificial Intelligence with highest honors from Technical University of Catalonia and a five-year degree in Computer Science from Technical University of Valencia. He worked on his Ph.D. at the Artificial Intelligence Research Institute of Spanish Council for Scientific Research. He has been a visiting researcher at the School of Mathematical Sciences at the University of Bath in the United Kingdom and at the School of Electrical Engineering and Computer Science at Oregon State University. https://twitter.com/aficionadohttp://www.linkedin.com/in/cisko